Recent Climate Trends and Drought Behavioral Assessment Based on Precipitation and Temperature Data Series in the Songhua River Basin of China

Precise analysis of spatiotemporal trends of temperature, precipitation and meteorological droughts plays a key role in the sustainable management of water resources in the given region. This study first aims to detect the long-term climate (monthly/seasonally and annually) trends from the historica...

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Bibliographic Details
Published in:Water resources management 2016-10, Vol.30 (13), p.4839-4859
Main Authors: Khan, Muhammad Imran, Liu, Dong, Fu, Qiang, Dong, Shuhua, Liaqat, Umar Waqas, Faiz, Muhammad Abrar, Hu, Yuxiang, Saddique, Qaisar
Format: Article
Language:English
Subjects:
Agriculture
Air temperature
Atmospheric Sciences
Civil Engineering
Climate
Climate change
Drought
Drought index
Droughts
Earth and Environmental Science
Earth Sciences
Environment
Freshwater
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
Hydrologic data
Hydrology
Hydrology/Water Resources
Laboratories
Nonparametric statistics
Precipitation
Precipitation (meteorology)
River basins
Rivers
Seasons
Slopes
Standardized precipitation index
Studies
Sustainability management
Temperature
Trends
Water resources management
Weather hazards
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Summary:Precise analysis of spatiotemporal trends of temperature, precipitation and meteorological droughts plays a key role in the sustainable management of water resources in the given region. This study first aims to detect the long-term climate (monthly/seasonally and annually) trends from the historical temperature and precipitation data series by applying Spearmen’s Rho and Mann-Kendall test at 5 % significant level. The measurements of both climate variables for a total period of 49 years (1965–2013) were collected from the 11 different meteorological stations located in the Songhua River basin of China. Secondly, the two well-known meteorological drought indices including the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) were applied on normalize data to detect the drought hazards at 3, 6, 9 and 12 month time scale in the study area. The analysis of monthly precipitation showed significant ( p  
ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-016-1456-x